Director, Internal AI & Data Science - job 37 of 39

As the Director of Internal AI & Data Science at Visa, your responsibilities include the design and development of systems needed for the collection, processing, and integration of both structured and unstructured data. You will lead a team of data scientists in applying advanced techniques to drive business impact, while also managing relationships with various stakeholders to communicate results and insights effectively.

To be considered for the Director of Internal AI & Data Science position at Visa, candidates should have extensive experience in data science, particularly in AI and machine learning. Proficiency in programming languages like Python and R is essential, and familiarity with industry-standard data science tools like TensorFlow or PyTorch will be highly beneficial. Additionally, strong leadership skills and a track record in managing teams will be critical for success in this role.

In this role, the Director of Internal AI & Data Science at Visa has the opportunity to influence business decisions by providing data-driven insights and recommendations to senior leadership. By translating complex data science concepts into actionable strategies, this position plays a pivotal role in aligning data initiatives with overall business goals.

The Director of Internal AI & Data Science at Visa will lead a team of skilled data scientists, focusing on fostering a culture of collaboration and innovation. This includes mentoring team members, ensuring high-quality deliverables, and driving the team's vision for data science capabilities that align with Visa's strategic objectives.

In this position, the Director of Internal AI & Data Science at Visa will work with a variety of data sources, including industry segment data across global markets, as well as public and commercial databases. This diverse array of data is integral to enriching Visa’s existing datasets, thereby enhancing business understanding and decision-making.

When answering this question, focus on specific projects you've led or contributed to that involved AI and machine learning. Highlight technologies used, challenges faced, and the outcomes of implementing these methodologies.

Discuss your approach to prioritization based on project urgency and impact. Mention any frameworks or tools you use to organize tasks and ensure deadlines are met while maintaining quality.

You can mention subscribing to relevant journals, attending conferences, joining professional networks, or taking online courses. Emphasize your commitment to continual learning to better serve your team and the company.

Provide examples of how you've successfully communicated complex data science concepts in an easily understandable manner. Highlight your ability to tailor messages to different audiences.

Share a specific example where your data analysis led to significant business decisions or outcomes. Use metrics to quantify the impact and explain your role throughout the project.

Elaborate on your inclusive leadership style, emphasizing collaboration, innovation, and fostering team growth. Provide examples of how you've supported your team's development.

Discuss your approach to assessing data quality, establishing data pipelines, and ensuring the integrity of integrated data. Mention any relevant tools or techniques you find effective.

Discuss your understanding of data privacy and ethical guidelines. Highlight the policies you prioritize and how you involve your team in ethical considerations during data projects.

Mention key languages such as Python and R, and explain their importance in data manipulation and analysis. You could also discuss the relevance of SQL for database management.

Show your understanding of Visa's values and strategic direction. Discuss how you would collaborate with various departments to ensure data science initiatives directly support organizational objectives.